As quantitative data become available for a particular form or function in the nervous system, it is advisable to attempt to assimilate the information into a comprehensive model of the underlying mechanisms and their interactions. This project consists of the development of such models and the necessary analytical and mathematical techniques for their implementation and testing in several areas of experimental investigation by LNLC members and other laboratories. Recent work uses the concepts of fractal geometry to characterize the shape of neurons, as their form changes in time or across classes. We found that the shape of several types of neurons is "fractal": the amount of detail that can be resolved is proportional to the scale of resolution, the complexity of neuronal form can be quantitated by its fractal dimension, and the paths of dendrites appear to be shaped by processes acting at a wide range of length scales. We have also apparently found a better way to resolve a complex shape into its sinusoidal components.